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In many countries, spent nuclear fuel is planned to be stored in a geological repos­itory. Before the final encapsulation, safety parameters such as decay heat, criti­cality, and dose rate need to be ensured. A gamma scan of the spent nuclear fuel assemblies in the pool can extract valuable information needed to verify or update the declared values before the encapsulation. Gamma scans can be used to esti­ mate values such as burnup, cooling time, or initial enrichment [1], but also decay heat [2]. This paper presents results from a full­energy peak area evaluation study of experimental gamma­ray spectra acquired from measurements using a high­purity germanium detector on 47 spent nuclear fuel assemblies from Sweden in 2016 and 2019. The assemblies chosen are UO2 fuel and represent a large span in cooling­ time, burnup, and initial enrichment [3]. The gamma spectra were acquired in the spent fuel pool of the Clab facility. As part of the measurement analysis, one wishes to determine the full­energy net peak areas associated with selected fission prod­ucts. This work presents results obtained using different methods to evaluate the full­energy peak areas, including the use of different background estimations.

In the determination of important safety parameters using gamma spectroscopy, it is crucial to consider uncertainties originating in the peak area analysis. The un­ certainty from the full­energy peak area without the background has been evaluated and compared between the different models.

This work studies the reproducibility of passive gamma spectroscopy measurements for spent nuclear fuels (SNFs). The fifty assemblies used for this study span over a variety of initial enrichments, burnups, and cooling times. These SNFs have been measured in two different gamma axial measurement campaigns. The net peak counts are determined for Cs-137, Eu-154 and Cs-134. Furthermore, a sensitivity analysis of the relative position of the SNF and the detector is performed. Most importantly, this work describes a methodology using an intrinsic self-calibration procedure that can be used to compare the relative activities of the radionuclides without the need for detailed knowledge about the measurement set-up and its properties. The reproducibility of the Cs-137 net peak count rate ranges between 2% and 4%. Systematic reproducibility of the ratio of Eu-154 and Cs-134 to Cs-137 is between 0,4% - 5 % using the intrinsic self-calibration method.

In the context of a geological repository for nuclear waste, fast and accurate predictions of decay heat are needed for different applications ranging from canister loading optimization to comparing decay heat predictions from state-of-the-art codes with experimental measurements. This work uses a large database of simulated pressurized water reactor (PWR) spent nuclear fuel (SNF) with an extensive range of fuel parameters to demonstrate that by using only the burnup, initial enrichment, and cooling time of the SNF, it is possible to predict the decay heat of a PWR SNF.

A linear interpolation model has been developed using the simulated data and tested on data from decay heat measurements using a calorimeter. The model code was also made publicly available [V. Solans, “Python Scriptfor the Prediction of Decay Heat from PWR Spent Nuclear Fuel Using Fuel Parameters,” Zenodo (2024)]. Theresults show that the decay heat can be well predicted, with the relative error between measurements and predictions ranging between 4% and 8%. After correcting for a systematic deviation between predictions and experimental results using the limited set of experimental measurement data available, the relative error can befurther reduced to 2% to 3%.

This research paper introduces a novel approach to predict the decay heat of spent nuclear fuel assemblies (SNFs) using data from non-destructive gamma and neutron measurements, addressing the challenge of ensuring safety in geological repositories. Because calorimetric measurements are time-consuming, it is envisioned that gamma and neutron measurements can be used for decay heat prediction before encapsulation. This paper analyses gamma and neutron data to extract key features, specifically the activities of Cs-137, Eu-154, and the total neutron count rate. A Gaussian process model is then employed to estimate SNF decay heat. The methodology involves training a prediction model on a calibrated simulated dataset designed to mimic real experimental conditions closely. The model is then successfully used to predict the decay heat for unseen experimental data. The results highlight the potential of using gamma and neutron measurements for reliable decay heat prediction. It is shown that the magnitude of the relative deviation obtained is 2–4 %. Furthermore, the study explores the impact of removing certain input features or adjusting their uncertainty levels on the decay heat prediction model precision, in particular for the Eu-154 activity and neutron count rate. This comprehensive methodology paves the way for applying these techniques to a larger experimental scale offering a significant advancement in the safety assessment of SNFs prior to encapsulation and long-term storage.